The Prospect of Artificial Intelligence in Chemical Process Industries
Abidemi Awojuyigbe Mentor: Emmanuel A. Dada Department of Chemical Engineering Introduction: Artificial intelligence is a subpart of computer science that focuses on developing programs to enable computers to perform tasks that usually require human intelligence. In this project, we shall explain AI in general, analyze the logic behind AI, and identify promising current and future AI application opportunities in chemical industries, where AI can be implemented to enhance chemical industries' operations. In this project, we shall focus on the implementation of artificial intelligence on a distillation column. Materials and Methods: For this study, we carried out an extensive literature review on AI applications in the chemical industries. We researched machine-learning applications to increase the efficiency of catalyst formation processes. This research focused on the significant impact and values of Artificial Intelligence in chemical industries over natural human intelligence. Deep learning was applied to solve high-level functions like modeling, simulation, and optimization of chemical processes. Results and Discussion: Artificial intelligence (AI) refers to the simulation of human intelligence in machines programmed to think like humans and mimic their actions. There are two kinds of AI: Artificial Narrow Intelligence (ANI), with example, in a smart speaker, self-driving car, and Artificial General Intelligence that can do anything humans can do. Machine Learning: It is the concept that gives a computer program able to learn and adapt to new data without human intervention or without being explicit. Machine learning is a field of artificial intelligence (AI) that keeps a computer's built-in algorithms current regardless of changes in the worldwide economy. Artificial Intelligence is beginning to make its way into the chemical industry; it is now being used to reduce chemical companies' carbon footprint. The chemical industry is now starting to adopt artificial intelligence to improve operational efficiency, reduce costs, and cut down greenhouse gas emissions. Application of AI in chemical process modeling: An AI-based approach to chemical modeling encompasses processes such as catalyst deactivation in reactors. The most common methods of artificial intelligence in chemical modeling are ANN and fuzzy logic. Application of AI in optimization in chemical processes: Chemical process optimization generally refers to finding the best solution from various operating variables' alternatives to maximize or minimize the desired objective. Application of AI in fault detection: The utilization of neural networks to identify faults is becoming increasingly sought in the chemical industry. Neural networks have a high potential for capturing non-linear relationships. Conclusions: We are currently researching ways to apply artificial intelligence, specifically on a distillation column in the chemical industry. We are working on using artificial intelligence to increase the efficiency of chemical processes in the chemical industry. This research would examine possible applications of artificial intelligence on a distillation column. We aim to analyze the logic behind artificial intelligence and identify potential applications in the chemical industries. References:
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